class StateModel { private val _state = MutableStateFlow(initial) val state = _state.asStateFlow() // read-only

Think of a val x: StateFlow as an asynchronous and observable counterpart of var x: T . Its most recent value is always available and, in fact, the most recent value is the only one that matters, so updating it is always possible without suspension.

As different kinds of shared flows replaced different kinds of broadcast channels the popular question is what going to happen with plain, regular channels? They are going to stay for many reasons. One reason is that channels are low-level primitives that are used to implement many complex flow operators.

Pandas library has a resample() function which resamples time-series data. The resample method in pandas is similar to its groupby method since it is essentially grouping by a specific time span.

But channels also have their application use-cases. Channels are used to handle events that must be processed exactly once. This happens in a design with a type of event that usually has a single subscriber, but intermittently (at startup or during some kind of reconfiguration) there are no subscribers at all, and there is a requirement that all posted events must be retained until a subscriber appears.

So here we have the average stock data displayed on the 31st of each month. Below is a complete list of the offset values. The list can be found in the pandas’ documentation.

To shift our data forward, we will pass the desired number of periods (or increments) through the shift() function, which in this case, needs to be a positive value. Let’s move our data forward by one period or index, which means that all values which earlier corresponded to row N will now belong to row N 1. Here is the output:

It appears that Maruti had a more or less steady increase in its stock price from 2004 to the mid-2018 window. There seems to be some drop in 2019, though. Let’s further analyze the data for the year 2018.

If you add a day or two it will add a day or two. But the date I put here is February 28th. That is different, right? In leap years we have 29 days in February and the other years we have 28 days in February.

Here, ‘Q-DEC’ means the quarter ends in December. There are four quarters in a year and the last quarter ends in December. But there are several industries out there who use January as the end of the 4th quarter or June as the 4th quarter.

Look, Here we changed the end of the 4th quarter to January! Feel free to check the start and end-month of q1. You will see the start month will be march instead of April. Because the first quarter runs from February to April.

Sometimes, it is desirable to shift or move the data forward or backward in time. This shifting is done along a time index by the desired number of time-frequency increments. Here is the original dataset without any shiftings.

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I was working telling me how he dressed for a date with his girlfriend of six months. “I can’t do a thing with my hair (he’d lost most of it),” he grinned. “But I make an effort — put on a collared shirt and nice shoes. I think it shows her respect.” It does.

With the state flow, the performance difference between a complex channel and a simple flow becomes quite apparent. An implementation of a state flow has allocation-free updates, which was not the case with a conflated broadcast channel.

Time resampling is a way to aggregate data with respect to a defined time period. We have the stock price data for each day, but this doesn’t make much sense if we want to see the trend for a financial institution. What is useful is the aggregated information for every month or every quarter. This helps the management to get an overview instantly and then make decisions based on this overview.

So there is a dip in stock prices around the last week of October and the first week of November. One could investigate it further by finding out if there was some special event on that day.